TY - GEN
T1 - Introduction of a Bayesian network builder algorithm personalized infectious disease risk prediction
AU - Vinarti, Retno Aulia
AU - Hederman, Lucy
N1 - Publisher Copyright:
Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
PY - 2018
Y1 - 2018
N2 - We introduce an algorithm for auto-generating a Bayesian Network (BN) structure from a knowledge-base represented as an ontology with rules. The ontology and rules represent the assumptions of infectious disease risk in the epidemiology domain. The resulting BN will be the computational model for an infectious disease risk prediction service. The BN structure consists of one child node, to represent the chosen infectious disease, with multiple parent nodes to represent the contexts which affect infection risk. Thus, this BN generation algorithm is constrained to a relatively simple structure. The algorithm generates a BN using the API of BN modeler software, Netica-J. We evaluate two aspects of the generated BN: the network structure and the conditional probability tables (CPTs). The validation result shows that the algorithm generates an isomorphic BN compared with the ontology and the CPTs are populated with consistent ratios from epidemiological rules. Furthermore, the generated BN has resulted in a personalized infectious disease risk prediction based on the personal attributes and their environments.
AB - We introduce an algorithm for auto-generating a Bayesian Network (BN) structure from a knowledge-base represented as an ontology with rules. The ontology and rules represent the assumptions of infectious disease risk in the epidemiology domain. The resulting BN will be the computational model for an infectious disease risk prediction service. The BN structure consists of one child node, to represent the chosen infectious disease, with multiple parent nodes to represent the contexts which affect infection risk. Thus, this BN generation algorithm is constrained to a relatively simple structure. The algorithm generates a BN using the API of BN modeler software, Netica-J. We evaluate two aspects of the generated BN: the network structure and the conditional probability tables (CPTs). The validation result shows that the algorithm generates an isomorphic BN compared with the ontology and the CPTs are populated with consistent ratios from epidemiological rules. Furthermore, the generated BN has resulted in a personalized infectious disease risk prediction based on the personal attributes and their environments.
KW - Bayesian Network
KW - Infectious Disease Risk
KW - Knowledge-Base
KW - Ontology
KW - Risk Prediction
UR - http://www.scopus.com/inward/record.url?scp=85046542027&partnerID=8YFLogxK
U2 - 10.5220/0006573301150126
DO - 10.5220/0006573301150126
M3 - Conference contribution
AN - SCOPUS:85046542027
T3 - HEALTHINF 2018 - 11th International Conference on Health Informatics, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
SP - 115
EP - 126
BT - HEALTHINF 2018 - 11th International Conference on Health Informatics, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
A2 - Zwiggelaar, Reyer
A2 - Gamboa, Hugo
A2 - Fred, Ana
A2 - Bermudez i Badia, Sergi
PB - SciTePress
T2 - 11th International Conference on Health Informatics, HEALTHINF 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
Y2 - 19 January 2018 through 21 January 2018
ER -